Embodiments of the invention relate generally to a system and method for predicting the excitation pattern of a deep brain stimulation (DBS), and more particularly to a system and method that predicts a future timing pattern of a DBS excitation signal and generates a time stamp log predictive of future active transmission periods of neurological excitation.
Deep brain stimulation (DBS) is used for treating disabling neurological symptoms and psychiatric disorders. The procedure uses a neurostimulator to deliver electrical stimulation to the brain by way of surgically implanted electrodes. Depending on the condition being treated, the electrodes can be used to target certain cells and chemicals within the brain or can be targeted toward areas of the brain that control movement or regulate abnormal impulses. In this later case, the electrical stimulation can be used to disrupt abnormal nerve signals that cause tremor and other neurological symptoms. Over the past 20 years, more than 100,000 Parkinson's disease, essential tremor, dystonia and obsessive-compulsive disorder patients have seen significant symptom relief due to DBS treatment. Evidence now accumulates indicating that patients with chronic pain, post-traumatic stress disorder, and obesity may also benefit from DBS treatments.
Despite the long history of DBS, its underlying principles and mechanisms are still not clear. In particular, the understanding of how the brain responds to different DBS excitation parameters, such as electrode choice, frequency, current/voltage and pulse width is limited. There is no real time feedback mechanism to let a clinician decide whether DBS has its intended effect or whether the stimulation parameters are optimal for each individual patient. The only current option is to watch the patient evolve over a significant period of time, often months, and determine thereafter if symptoms improve. Feedback in the form of qualitative or quantitative measurements of brain response to DBS may aid in optimizing the DBS excitation parameters for treating conditions such as dystonia or depression.
Functional magnetic resonance imaging (fMRI) is one of the few non-invasive tools that could be used for such feedback. In particular, fMRI might be used to provide a quick and efficient feedback mechanism by highlighting areas of brain activity related to DBS stimulation and allowing optimization of DBS stimulation parameters in close to real time. However, fMRI is currently not easily achievable in patients with implanted DBS pulse generators due to the longstanding FDA restriction that prohibits patients with implanted DBS pulse generators from undergoing MRI.
Recent label changes for Medtronic® DBS hardware permit patients with internalized pulse generator hardware to undergo MRI during active DBS. While DBS electrodes can be cycled ON and OFF during a given DBS, there is no way to know whether the DBS excitation cycle is in the ON or OFF condition when the patient is inside the MRI scanner because the programming of the DBS device can only be done outside the MRI scanner. Even if the parameters of the DBS were known prior to fMRI acquisition, a multi-second time lag occurs during which the stimulation parameters are communicated from the controller to the pulse generator and thereafter from the pulse generator to the electrodes resulting in differences between the requested and measured stimulation periods. This communication time lag and the long time interval between the pulse generator programming and actual fMRI onset can lead to large errors in assessing the stimulation state, which can cause significant drops in fMRI sensitivity. Consequently, fMRI imaging data cannot be properly binned corresponding to ON and OFF conditions of the DBS excitation cycle.
It would therefore be desirable to have a system and method capable of accurately detecting the timing of the excitation pattern of a DBS and predicting a future timing pattern of the excitation pattern. It would also be desirable for such a system and method to generate an output from the future timing pattern in the form of a time stamp log to permit medical images acquired during DBS excitation to be binned in a manner corresponding to the DBS excitation. It would also be desirable for such a system and method to enable medical data acquisition to be synchronized with the ON and OFF conditions of a DBS excitation cycle such that brain regions activated as a consequence of the DBS may be identified in the acquired medical data. It would further be desirable to produce an output representative of the DBS excitation pattern to facilitate analysis of the health of the DBS system.